This folder contains the data and code to reproduce the data and figures of the miRNA-mRNA interaction in breast cancer subtypes

### Data

Inside the data folder we have:
- `GSE19783.RData`: ESet object contaning miRNA and mRNA expression and phenotypes downloaded from GEO using R package "GEOquery"
- `GSE19783_miRNA_mRNA_expression.txt`: paired miRNA and mRNA expression data for 101 breast cancer samples that were used to generate sample-specific BONOBO networks
- `GSE19783_phenotype.txt`: subject phenotypes including breast cancer type and survival information

### Code

In `src` we have the R code to reproduce all the analyses in the paper. 
- `GSE19783_join_edges.R`: combine sample-specific bipartite networks into a single matrix where rows correspond to network edges and columns correspond to samples
- `GSE19783_miRNAmRNA_coexpression_subtype_comparison.R`: limma model to identify genes that are significantly correlated with miRNAs across different breast cancer subtypes
- `GSE19783_mRNAgene_survival.R`: Cox proportional hazard model for survival analysis to identify biological pathways for which the corresponding correlation with mIRNAs significantly predict survival outcome.
- `lumA_vsLumB_immuneNetwork.R`: visual representation of the top 50 miRNA-mRNa edges that are most different between Luminal A and Luminal B breast cancer subtypes.
- `lumA_vs_lumB_limma_edge.R`: limma model to identify miRNA-mRNa edges that are significantly different between Luminal A and Luminal B breast cancer subtypes.
- `miRNA_breastCancer_dataPrep.R`: Data preprocessing and filtering to prepare for network construction
- `miRNA_mRNA_bonobo_compute_indegree.R`: Compute overall degree, miRNA-specific degree and mRNA-specific degree for each node in the network

### Results 

- `indegree_all.txt`: overall degree (sum of all edges) for each node in the network
- `indegree_miRNA.txt`: miRNA-specific degree (sum of all edges connected to miRNAs alone) for each node in the network
- `indegree_mRNA.txt`: mRNA-specific degree (sum of all edges connected to mRNAs alone) for each node in the network


